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ijs-6315
Elastic electron scattering from 11Li and 12Be exotic nuclei in the framework of the binary cluster model
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The ground state densities of unstable neutron-rich 11Li and 12Be exotic nuclei are studied in the framework of the binary cluster model (BCM). The internal densities of the clusters are described by the single particle harmonic oscillator wave functions. The long tail performance is clearly noticed in the calculated neutron and matter density distributions of these nuclei. The structures of the two valence neutrons in 11Li and 12Be are found to be mixed configurations with dominant (1p1/2)2. Elastic electron scattering proton form factors for 11Li and 12Be are studied using the plane wave Born approximation (PWBA). It is found that the major difference between the calculated form factors of unstable nuclei [11Li, 12Be] and those of stable nuclei [7Li, 9Be] is the difference in the center of mass correction which depends on the mass number and the size parameter . The reaction cross sections for 11Li and 12Be are studied by means of the Glauber model with an optical limit approximation using the ground state densities of the projectile and target, where these densities are described by single Gaussian functions. The calculated reaction cross sections of 11Li and 12Be at high energy are in good agreement with experimental data. The analysis of the present study supports the halo structure of these nuclei.

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Publication Date
Sun May 26 2019
Journal Name
Iraqi Journal Of Science
Bayesian Estimation for Two Parameters of Gamma Distribution under Generalized Weighted Loss Function
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This paper deals with, Bayesian estimation of the parameters of Gamma distribution under Generalized Weighted loss function, based on Gamma and Exponential priors for the shape and scale parameters, respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation. Based on Monte Carlo simulation method, those estimators are compared in terms of the mean squared errors (MSE’s).

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Publication Date
Sat Dec 11 2021
Journal Name
Engineering, Technology & Applied Science Research
Post-Fire Behavior of Non-Prismatic Beams with Multiple Rectangular Openings Monotonically Loaded
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The main objective of this paper is to study the behavior of Non-Prismatic Reinforced Concrete (NPRC) beams with and without rectangular openings either when exposed to fire or not. The experimental program involves casting and testing 9 NPRC beams divided into 3 main groups. These groups were categorized according to heating temperature (ambient temperature, 400°C, and 700°C), with each group containing 3 NPRC beams (solid beams and beams with 6 and 8 trapezoidal openings). For beams with similar geometry, increasing the burning temperature results in their deterioration as reflected in their increasing mid-span deflection throughout the fire exposure period and their residual deflection after cooling. Meanwhile, the existing ope

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Publication Date
Fri Jan 01 2016
Journal Name
Ieee Access
Towards an Applicability of Current Network Forensics for Cloud Networks: A SWOT Analysis
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In recent years, the migration of the computational workload to computational clouds has attracted intruders to target and exploit cloud networks internally and externally. The investigation of such hazardous network attacks in the cloud network requires comprehensive network forensics methods (NFM) to identify the source of the attack. However, cloud computing lacks NFM to identify the network attacks that affect various cloud resources by disseminating through cloud networks. In this paper, the study is motivated by the need to find the applicability of current (C-NFMs) for cloud networks of the cloud computing. The applicability is evaluated based on strengths, weaknesses, opportunities, and threats (SWOT) to outlook the cloud network. T

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Engineering
Hydrodesulfurization of Iraqi Atmospheric Gasoil by Ti-Ni-Mo/γ-Al2O3 Prepared Catalyst
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This study investigates the improvement of Iraqi atmospheric gas oil characteristics which contains 1.402 wt. % sulfur content and 16.88 wt. % aromatic content supplied from Al-Dura Refinery by using hydrodesulfurization (HDS) process using Ti-Ni-Mo/γ-Al2O3 prepared catalyst in order to achieve low sulfur and aromatic saturation gas oil. Hydrodearomatization (HDA) occurs simultaneously with hydrodesulfurization (HDS) process. The effect of titanium on the conventional catalyst Ni-Mo/γ-Al2O3 was investigated by physical adsorption and catalytic activity test.Ti-Ni-Mo/γ-Al2O3 catalyst was prepared under vacuum impregnation condition to ensure efficient pr

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Publication Date
Mon Sep 23 2019
Journal Name
Al-kindy College Medical Journal
Primary Hydatid Cyst of Parotid Gland: A Rare Case Diagnosed by Computed Tomography
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Hydatid disease is a zoonotic infection caused by Echinococcus species. The cystic form of this infection mostly involves liver and lung. Hydatid disease of the parotid gland even in endemic regions is a very rare entity that may be easily overlooked in daily practice. Herein, I present a case report of a 60-year-old Iraqi female patient who presented with a progressively painless mass in her right parotid. It was diagnosed radiologically as a hydatid cyst and was excised successfully. Histopathologic examination of the resected specimen confirmed the hydatid cyst. This case emphasizes the importance of considering hydatidosis in the differential diagnosis of any parotid mass, especially in endemic countries.

 

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Publication Date
Fri Jun 24 2022
Journal Name
Iraqi Journal Of Science
Application of 2D Electrical Resistivity Imaging Technique for Detecting Soil Cracks: Laboratory Study
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Cracking of soils affects their geotechnical properties and behavior such as soil strength and stability. In this paper, 2D Electrical Resistivity Imaging Method, as a non-invasive technique, was adopted to investigate the effect of soil cracks of a centemetric scale on resistivity of sandy soil. The electrical resistivity measurements were carried out using ABEM SAS 300C Terrameter system at a laboratory scale using Wenner array. The measurements were interpreted using horizontal profiles, forward modeling and 2D inverse resistivity sections. The results showed that soil cracks cause significant changes in soil resistivity. These changes can be attributed to the high resistivity contrast between the highly resistive air-filled cracks an

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Publication Date
Mon Aug 01 2016
Journal Name
Asian Journal Of Biological And Life Science
Fumigant Toxicity of callistemon viminalis Essential Leaves Oils against Vinegar Fly, Drosophila melanogaster
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Publication Date
Wed Apr 24 2024
Journal Name
Cogent Arts & Humanities
Women’s health on social media: a corpus stylistic study of Pink October campaigns
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Publication Date
Fri Jan 31 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Radiographic follow up for clinical cases of mandibular implant retained overdenture MIR-OD
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Background: The use of osseointegrated fixtures in dentistry has been demonstrated both histologically and clinically to be beneficial in providing long term oral rehabilitation in completely edentulous individual. Most patients suffer from denture instability; particularly with mandibular prosthesis, the use of dental implant will be benefit significantly from even a slight increase in retention. The concept of implanting two to four fixtures in a bony ridge to retain a complete denture prosthesis appealing therefore, as retention, stability and acceptable economic compromise to the expanse incurred with the multiple fixture supported fixed prosthesis. Materials and methods in this study the sample were eight patients selected from a hosp

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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